CoVPN Cross-Protocol Analyses

项目摘要 该提案概述了新冠肺炎预防网络疫苗的科学议程 统计和数据管理中心(SDMC)，执行跨协议工作，以支持 新冠肺炎三期疗效试验。 随着新冠肺炎的全球流行，我们认识到对修改新冠肺炎的疫苗的重大需求 SARS-CoV-2感染者。为了弥补这一差距，HVTN SDMC加入了其他4个国家研究所 卫生部(NIH)临床试验网络组成CoVPN，这是一个致力于开发 全球有效的SARS-CoV-2疫苗。 CoVPN SDMC的创新和这项工作的优势包括我们的集体经验 在疫苗评估，特别是免疫相关性评估的统计方法方面的小组领导者，以及 我们与CoVPN领导中的临床和实验室小组建立了长期的关系 采用和利用统计方法来评估针对SARS-CoV-2其他病原体的疫苗。 例如，用于评估多种正式定义的保护相关因素的因果推理方法 包括疫苗效力的相关因素、疫苗效力的中介因素和随机干预对疫苗效力的影响 疫苗的效力。

Project Abstract This proposal outlines the scientific agenda for the COVID-19 Prevention Network (CoVPN) Vaccines Statistical and Data Management Center (SDMC) for implementation of cross-protocol work in support of COVID-19 phase 3 efficacy trials. With the global COVID-19 pandemic, we recognize a significant need for vaccines that modify COVID-19 in SARS-CoV-2 infected individuals. Addressing this gap, the HVTN SDMC has joined 4 other National Institute of Health (NIH) clinical trial networks to form the CoVPN, an enhanced network dedicated to developing globally effective vaccines for SARS-CoV-2. The innovation of the CoVPN SDMC and advantages to this work include the collective experience of our group- leader in statistical methods in vaccine evaluation, especially immune correlates assessment, and the long-standing relationships we have with the clinical and lab groups in the CoVPN lead Adapting and leveraging statistical methods for evaluating vaccines against other pathogens to SARS-CoV-2. E.g. causal inference methods for evaluating multiple types of formally defined correlates of protection including correlates of vaccine efficacy, mediators of vaccine efficacy, and stochastic-intervention effects on vaccine efficacy.